Related papers: HIVE-4-MAT: Advancing the Ontology Infrastructure …
HIVE4MAT is a linked data interactive application for navigating ontologies of value to materials science. HIVE enables automatic indexing of textual resources with standardized terminology. This article presents the motivation underlying…
Researchers across nearly every discipline seek to leverage ontologies for knowledge discovery and computational tasks; yet, the number of machine readable materials science ontologies is limited. The work presented in this paper explores…
In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the…
Ontologies are widely used in materials science to describe experiments, processes, material properties, and experimental and computational workflows. Numerous online platforms are available for accessing and sharing ontologies in Materials…
Information technology and data science development stimulate transformation in many fields of scientific knowledge. In recent years, a large number of specialized systems for information and knowledge management have been created in…
The rapidly increasing number of scientific documents available publicly on the Internet creates the challenge of efficiently organizing and indexing these documents. Due to the time consuming and tedious nature of manual classification and…
Modern information systems are changing the idea of "data processing" to the idea of "concept processing", meaning that instead of processing words, such systems process semantic concepts which carry meaning and share contexts with other…
Ontology Matching (OM), is a critical task in knowledge integration, where aligning heterogeneous ontologies facilitates data interoperability and knowledge sharing. Traditional OM systems often rely on expert knowledge or predictive…
The use of Semantic Technologies - in particular the Semantic Web - has revealed to be a great tool for describing the cultural heritage domain and artistic practices. However, the panorama of ontologies for musicological applications seems…
Ontology Matching (OM) plays an important role in many domains such as bioinformatics and the Semantic Web, and its research is becoming increasingly popular, especially with the application of machine learning (ML) techniques. Although the…
Ontology can be used for the interpretation of natural language. To construct an anti-infective drug ontology, one needs to design and deploy a methodological step to carry out the entity discovery and linking. Medical synonym resources…
Ontology alignment process is overwhelmingly cited in Knowledge Engineering as a key mechanism aimed at bypassing heterogeneity and reconciling various data sources, represented by ontologies, i.e., the the Semantic Web cornerstone. In such…
Homogeneous unstructured data (HUD) are collections of unstructured documents that share common properties, such as similar layout, common file format, or common domain of values. Building on such properties, it would be desirable to…
Successful biomedical relation extraction can provide evidence to researchers and clinicians about possible unknown associations between biomedical entities, advancing the current knowledge we have about those entities and their inherent…
When developing devices, architectures and services for the Internet of Medical Things (IoMT) world, manufacturers or integrators must be aware of the security requirements expressed by both laws and specifications. To provide tools guiding…
Ontologies are widely used for representing domain knowledge and meta data, playing an increasingly important role in Information Systems, the Semantic Web, Bioinformatics and many other domains. However, logical reasoning that ontologies…
Multimodal retrieval models fail on reasoning-intensive queries where images (diagrams, charts, screenshots) must be deeply integrated with text to identify relevant documents -- the best multimodal model achieves only 27.6 nDCG@10 on…
This study is dedicated to assessing the capabilities of large language models (LLMs) such as GPT-3.5-Turbo, GPT-4, and GPT-4-Turbo in extracting structured information from scientific documents in materials science. To this end, we…
The information retrieval systems that are present nowadays are mainly based on full text matching of keywords or topic based classification. This matching of keywords often returns a large number of irrelevant information and this does not…
Ontologies serve as a one of the formal means to represent and model knowledge in computer science, electrical engineering, system engineering and other related disciplines. Ontologies within requirements engineering may be used for formal…